AI is making waves across industries, opening up numerous opportunities. However, crafting a powerful AI strategy is a different ballgame than a traditional business strategy. It involves incorporating a strategy and aligning it with your business goals – a process that demands resources and long-term planning. But why should you care about building an AI strategy in the first place?

According to PwC, AI could contribute a whopping $15.7T to the global economy by 2030. The IBM Global AI Adoption Index 2022 shows that 25% of companies already use AI to address talent shortages. However, leveraging this technology is more than integrating existing solutions and applications. It's about understanding the specific needs of your business and how to manage to implement these AI and ML business solutions efficiently.

This is where AI strategy consulting services step in. But what's the connection between data strategy and the broader AI framework? And how can consulting help overcome the hurdles in creating AI-driven business solutions? Let’s find out.

What is AI strategy consulting?

At its core, AI strategy refers to a plan that outlines how an organization will use AI technologies to achieve its business objectives and gain a competitive edge. It involves a comprehensive understanding of AI's potential applications and the technical, operational, and ethical considerations that come with it.

In essence, an ideal AI strategy should answer the following key questions:

  1. What are the organization's goals for AI? These can be varied, such as improving operational efficiency, boosting customer satisfaction, or driving innovation in products and services.
  2. Where and how can AI be applied within the organization? This involves identifying the areas within the business that could benefit from AI and understanding how different solutions, such as Machine Learning, Natural Language Processing, and Robotic Process Automation can be implemented.
  3. What resources are needed to implement AI? It considers the infrastructure, technical skills, and data required to develop, deploy, and maintain AI solutions.
  4. How can the organization manage the risks and ethical implications of AI? This question addresses the potential challenges related to data privacy, bias in AI algorithms, job displacement, and other ethical concerns.

Once an organization has a clear intent to establish an AI strategy, this is where consulting comes into play. AI strategy consultants provide a blend of technical expertise and strategic insight, helping businesses to:

  • understand their current state of AI readiness;
  • define a vision for AI adoption;
  • conduct PoC;
  • build a roadmap and propose reasonable timelines;
  • propose team composition and associated costs;
  • conduct the AI/ML solutions architecture review;
  • manage the related risks;
  • ultimately implement AI solutions that align with their business objectives.

AI strategy components

What is the role of data strategy in shaping the AI strategy?

AI solutions rely heavily on data to train models, derive insights, and make predictions. AI implementations would struggle to deliver expected outcomes without a solid data strategy. For this reason, it’s essential to discuss the role of data strategy and its integral parts, including:

  • Data collection
  • Storage and management
  • Analysis and processing
  • Governance

In the initial phase of developing a broader AI strategy, it's essential to focus on data collection. Organizations need to identify relevant data sources, both internal and external, that can feed into their AI systems. Internal data could include everything from sales and transactional data to customer service records, while external data could come from public databases and more. It's crucial to use reliable data sources and ensure that the data collected is representative of the real-world scenarios the AI system will encounter.

Data storage and management is the next step in the chain. As AI technologies require a large volume of data, organizations must have the appropriate infrastructure to store and manage this data effectively. It includes the use of Cloud solutions and Big Data solutions, which offer scalability and flexibility for handling large datasets.

Then comes the stage of data analysis and processing. The collected data has to be cleaned, structured, and analyzed to extract valuable insights. Techniques like Machine Learning and statistical analysis are employed to identify patterns, correlations, and trends within the data. This stage is critical as the quality and relevance of insights drawn here directly influence the decision-making capabilities of AI systems.

Lastly, any effective data strategy must address data governance. It covers the policies, procedures, and standards to ensure ethical and lawful data use. Data governance includes privacy policies to protect sensitive information and procedures for compliance with data protection regulations such as GDPR. In an age where data breaches are becoming increasingly common, maintaining robust data governance is a legal requirement and a critical factor in building trust with customers and stakeholders.

Given the complexity and importance of these elements, partnering with a reputable AI strategy consulting provider becomes a top priority. At N-iX, we deeply understand data management best practices and the specific challenges associated with AI technologies. In aggregate, this knowledge can guide our clients in creating a data strategy that is robust, effective, and aligned with their broader business objectives.

Let’s discover one example where designing a data strategy has helped our client to leverage their data more efficiently and drive the potential for AI-powered initiatives.

role of data in shaping AI strategy

The success story of designing a data strategy

As a comprehensive e-commerce provider, cleverbridge strives to meet every customer's needs. One such need arose from their largest customer — the desire for a more effective analytics solution that could provide visually appealing data. The challenge for cleverbridge was to enhance their tool that provides subscription reports, encompassing revenue and new customer numbers, and supplement it with more visually informative data.

We partnered with cleverbridge to design a data strategy with a clear implementation plan of a reporting solution using Power BI. This approach involved an extensive Product Discovery Phase where N-iX's team interviewed client stakeholders and thoroughly examined existing processes. The N-iX team leveraged the insights from this discovery phase to build a modern data platform based on AWS and establish effective data governance.

Building a robust data strategy is paramount for any business to leverage data analytics and AI solutions effectively. A well-crafted data strategy can enhance business decision-making, improve customer insights, and optimize operations. N-iX played a pivotal role in designing a comprehensive data strategy for cleverbridge, which involved understanding the existing processes, gathering requirements, and devising an implementation plan. This strategic roadmap became the backbone of the enhanced reporting solution that cleverbridge sought to offer its customers.

Value delivered by N-iX:

The comprehensive data analytics solution developed by N-iX enabled cleverbridge to meet their needs and broaden their services by integrating the solution into their product offering. The designed solution also led to several additional benefits, including: 

  • Enhanced their value proposition by offering a universal reporting solution, which attracted more customers;
  • Improved information security through the effective data governance of the developed data platform;
  • Boosted business decision-making capabilities by using the solution internally to gain insights into client performance.

AI strategy consulting roadmap

AI strategy consulting services are indispensable in supporting businesses on their AI journey. These services cover various areas, each addressing distinct needs and challenges that businesses may encounter while developing their AI strategy. Our specialists differentiate the following consulting steps that form a more comprehensive AI roadmap. 

  1. AI readiness assessment. This is typically the starting point for organizations embarking on their AI journey. AI strategy consulting specialists comprehensively assess the organization's readiness to adopt and implement AI technologies. This assessment involves the review of the existing IT infrastructure, data quality and management, staff skill levels, and the strategic alignment of AI with business objectives.
  2. AI strategy development. At N-iX, our Machine Learning strategy consulting specialists work closely with stakeholders to identify the strategic goals AI-powered solutions could help achieve. The AI strategy outlines the specific technologies, their proposed applications within the organization, and the resources and infrastructure required. At this stage, our team also delivers a roadmap for implementation and a framework for measuring the success of AI-powered initiatives.
  3. AI implementation planning and support. It involves choosing the right technologies, designing and developing solutions, integrating AI into existing systems, and testing the solutions for effectiveness. Our consulting specialists provide guidance and support throughout this process, ensuring the technical implementation aligns with the strategic vision. We can also offer project management support to oversee the implementation process, ensuring it adheres to the planned timelines and budgets.
  4. Training and change management. The introduction of AI in an organization often necessitates changes in business processes and requires upskilling the workforce. It’s necessary to facilitate this transition by developing a change management strategy. Specifically, the strategy includes employee training, helping them understand AI technologies and how to use them effectively. Consultants, in turn, also work with management to foster a culture that embraces AI and data-driven decision-making, which is crucial for the long-term success of AI initiatives.
  5. Ongoing support. The AI journey doesn't end with the initial draft of a strategy or assessment. Consultants provide continuing support, helping companies monitor the performance of their solutions, troubleshoot any technical issues, and adapt to changes in the business environment or AI technologies. We also assist in continuously refining the strategy and implementation based on performance feedback and evolving business goals.

AI strategy consulting roadmap

By offering these extensive services, our AI consulting services provide valuable support to businesses at every stage of their AI journey. With our unique blend of business acumen and technical expertise, AI strategy consulting help businesses navigate the complexities of adoption, maximize the value, and use AI and ML as competitive differentiators.

Keep reading: Machine Learning consulting: From a concept to measurable business value

Principles to follow in building the AI strategy

Creating a successful AI strategy involves more than just understanding the technicalities of AI. It requires a deep appreciation of business goals, ethical considerations, and a forward-thinking approach. The following principles should guide the design of any AI transformation strategy:

  1. Alignment with business objectives. A strategy should not exist in isolation but should align with the broader business objectives. According to Deloitte’s State of AI in the Enterprise report, a mismatch between the business goals and AI strategy can diminish the ability to use AI to accelerate product release or secure supply chains. In other words, the best AI strategies “begin without mentioning the AI.” Thus, a solid strategy can only deliver value, improve efficiency, enhance customer service, or develop new products or services by understanding the organization's strategic goals. Thus, each AI initiative should be linked to a specific, measurable business outcome.
  2. Data governance and security. Effective data governance and security practices are essential. It involves maintaining the quality and accuracy of data and ensuring its protection against breaches and misuse. Compliance with data regulations should be a top priority, along with continuous monitoring and improvement of data management practices.
  3. Scalability and adaptability. The strategy should be designed to be scalable and adaptable, considering the rapid pace of advancements in AI technology. Businesses should plan how their initiatives can be scaled up as their capabilities and needs grow. Companies should also know how to adapt to new developments in AI technology or changes in the business environment.
  4. Ethical considerations. AI's growing influence underscores the importance of ethical considerations in designing an AI strategy. It includes designing AI systems that minimize bias, provide transparency in their decision-making processes, and ensure accountability. You should also consider the potential societal impact of their AI initiatives and take steps to mitigate any negative consequences.
  5. Collaboration and partnership. Designing a strategy involves venturing into new and complex territory. Experienced strategy consultants like N-iX can provide valuable resources, technical expertise, and fresh perspectives. Collaborative efforts can be particularly beneficial in navigating the complexities and uncertainties associated with building a custom AI strategy.

You can start working on the strategy design once you follow these principles in close cooperation with our Data team. In particular, the strategy will meet their unique needs and goals and address AI's wider ethical and societal implications. A well-designed strategy can serve as a roadmap, guiding businesses and helping them leverage the power of AI responsibly and effectively.

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Closing thoughts

AI strategy consulting serves as a compass, guiding businesses through the complexities of AI adoption and helping them navigate their AI journey. From assessing readiness and developing a comprehensive strategy to offering support during implementation and ensuring continuous optimization, AI consultants at N-iX play a pivotal role in ensuring your successful transformation.

In the age of AI, businesses must be willing to adapt, innovate, and embrace change. With a sound AI strategy and skilled specialists' support, you can successfully embark on your AI journey, maximize the value derived from AI, and stay competitive in the digital era. The future of AI is here, and it’s up to us to seize the opportunities it presents.

Why choose N-iX as your provider of AI strategy consulting services?

  • N-iX stands as a premier Big Data provider, demonstrating over a decade of proficiency in data-related services;
  • The company boasts a sizable team of over 200 data experts, all skilled in multiple areas such as Big Data, AI/ML, legacy migration, Data Science, and Data Analytics;
  • The services offered by N-iX extend to Artificial Intelligence consulting and the implementation of intelligent solutions powered by AI and ML, covering a broad spectrum of applications;
  • Deep learning, predictive analytics, customer behavior analysis, risk allocation and mitigation, and predictive maintenance are among the AI and ML applications that N-iX offers;
  • N-iX's AI and ML services have attracted a range of clients, including Orbus Software, Gogo, Lebara, AVL, cleverbridge, and Fortune 500 companies;
  • N-iX strictly adheres to industry regulations and standards such as PCI DSS, ISO 9001, ISO 27001, and GDPR.

Have a question?

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N-iX Staff
Rostyslav Fedynyshyn
Head of Data and Analytics Practice

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